Choices and Outcomes in Assignment Mechanisms: The Allocation of Deceased Donor Kidneys

While the mechanism design paradigm emphasizes notions of efficiency based on agent preferences, policymakers often focus on alternative objectives. School districts emphasize educational achievement, and transplantation communities focus on patient survival. It is unclear whether choice‐based mechanisms perform well when assessed based on these outcomes. This paper evaluates the assignment mechanism for allocating deceased donor kidneys on the basis of patient life‐years from transplantation (LYFT). We examine the role of choice in increasing LYFT and compare realized assignments to benchmarks that remove choice. Our model combines choices and outcomes in order to study how selection affects LYFT. We show how to identify and estimate the model using instruments derived from the mechanism. The estimates suggest that the design in use selects patients with better post‐transplant survival prospects and matches them well, resulting in an average LYFT of 9.29, which is 1.75 years more than a random assignment. However, the maximum aggregate LYFT is 14.08. Realizing the majority of the gains requires transplanting relatively healthy patients, who would have longer life expectancies even without a transplant. Therefore, a policymaker faces a dilemma between transplanting patients who are sicker and those for whom life will be extended the longest.

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Publication Details

Journal
Econometrica
Published
2025-01-01
DOI
https://doi.org/10.3982/ecta20203
Citations
2
Primary Topic
Organ Donation and Transplantation
Type
article
Field-Weighted Citation Impact
3.76

Funders

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article

Choices and Outcomes in Assignment Mechanisms: The Allocation of Deceased Donor Kidneys

Paulo Somaini, Nikhil Agarwal, Charles Hodgson
2 citations
Econometrica
Organ Donation and Transplantation
3.76
article

Choices and Outcomes in Assignment Mechanisms: The Allocation of Deceased Donor Kidneys

Paulo Somaini, Nikhil Agarwal, Charles Hodgson
article en
2 citations

Abstract

While the mechanism design paradigm emphasizes notions of efficiency based on agent preferences, policymakers often focus on alternative objectives. School districts emphasize educational achievement, and transplantation communities focus on patient survival. It is unclear whether choice‐based mechanisms perform well when assessed based on these outcomes. This paper evaluates the assignment mechanism for allocating deceased donor kidneys on the basis of patient life‐years from transplantation (LYFT). We examine the role of choice in increasing LYFT and compare realized assignments to benchmarks that remove choice. Our model combines choices and outcomes in order to study how selection affects LYFT. We show how to identify and estimate the model using instruments derived from the mechanism. The estimates suggest that the design in use selects patients with better post‐transplant survival prospects and matches them well, resulting in an average LYFT of 9.29, which is 1.75 years more than a random assignment. However, the maximum aggregate LYFT is 14.08. Realizing the majority of the gains requires transplanting relatively healthy patients, who would have longer life expectancies even without a transplant. Therefore, a policymaker faces a dilemma between transplanting patients who are sicker and those for whom life will be extended the longest.

EconometricaVol. 93(2)
Yale University (US), Stanford University (US)
Alfred P. Sloan Foundation
Openalex Percentile: Top 9%
Organ Donation and Transplantation
3.76
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